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Large Shareholder Entrenchment and Performance: Empirical Evidence from Canada

2007· article· en· W2052161560 on OpenAlexaffabout
Yves Bozec, Claude Laurin

Bibliographic record

VenueJournal of Business Finance &amp Accounting · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsShareholderVotingIncentiveCash flowBusinessMonetary economicsAgency costInsiderEmpirical evidenceAgency (philosophy)AccountingCorporate governanceEconomicsFinanceMicroeconomicsLawPolitics

Abstract

fetched live from OpenAlex

Abstract: Recent empirical evidence indicates that the largest publicly traded companies throughout the world have concentrated ownership. This is the case in Canada where voting rights are often concentrated in the hands of large shareholders, mostly wealthy families. Such concentrated ownership structures can generate specific agency problems, such as large shareholders expropriating wealth from minority shareholders. These costs are aggravated when large shareholders don't bear the full costs of their decisions because of the presence of mechanisms (dual class voting shares, pyramids) which lead to voting rights being greater than the cash flow rights (separation). We assess the impact of separation on various performance metrics while controlling for situations when the large shareholder has (1) the opportunity to expropriate (high free cash flows in the firm) and (2) the incentive to expropriate (low cash flow rights). We also control for when the large shareholder has the power to expropriate (high voting rights, outright control and insider management) and for the presence of family ownership. The results support our hypotheses and indicate that firm performance is lower when large shareholders have both the incentives and the opportunity to expropriate minority shareholders.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.152
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.004
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.242
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations166
Published2007
Admission routes2
Has abstractyes

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